Compile and Run the DataStage job.
编译并运行DataStage作业。
Save the DataStage job and compile it.
保存DataStage作业并编译它。
Compiling and running the DataStage job.
编译和运行DataStage作业。
Create a DataStage job to access the data.
创建DataStage作业以访问数据。
DataStage will attempt to execute your job.
DataStage将尝试执行作业。
Saving the metadata definitions in DataStage
将元数据定义保存到 DataStage 中
Figure 3 shows the layout of the DataStage job.
图3显示了DataStage作业的布局。
The stage reads the data from the DataStage input link.
工作台从DataStage输入链接读取数据。
The RDP DataStage project utilizes parameter value sets.
RDPDataStage项目利用参数值组。
You can see the layout of the DataStage job in Figure 9.
您可以在图9中看到DataStage作业的布局。
The tr4j library comes bundled with the DataStage installer.
tr4j库与DataStage安装程序捆绑在一起。
Following is the DataStage Job and corresponding Director Log.
下面是DataStage作业及其对应的Director日志。
Step 2: Create a DataStage parallel job and outline its contents.
步骤2：创建DataStage并行作业并概括其内容。
Information is stored in table definitions in the DataStage repository.
这些信息存储在DataStage储存库中的表定义中。
DataStage can dramatically simplify tasks from development to maintenance.
DataStage可以大大简化从开发到维护的任务。
From the DataStage palette, drag the following three stages to the canvas.
从DataStage调色板中拖出以下三个阶段到画布。
These parallel features enable DataStage to achieve very high performance.
这些并行特性能让DataStage实现高性能。
Additionally, learn important tips about using the DataStage DB2 Connector.
另外，还将了解使用DataStageDB 2Connector的重要技巧。
You now have a parallel job skeleton for the first part of your DataStage job.
现在，您的DataStage作业的第一部分已经具有一个并行作业骨架。
Similar to the DataStage stages, the assembly steps always iterate input lists.
与DataStage stages类似的是，程序集步骤总是迭代输入列表。
Follow the standard DataStage procedures to compile, validate, and run your job.
按照标准DataStage步骤编译、验证和运行作业。
These differences can arise between operating systems, databases, and DataStage.
这些差别可能会在不同的操作系统、数据库和DataStage之间产生。
The IIS server contained both the server and client for developing the DataStage job.
IIS服务器同时包含了用于开发DataStage 作业的服务器和客户机。
You can also save the table definitions to the DataStage repository for future usages.
还可以将表定义保存到DataStage存储库中，以备将来使用。
There are multiple ways to perform this transformation in DataStage with the XML stage.
在DataStage中通过XMLstage有多种方式可执行该转换。
As you might expect, there are several ways to build a DataStage job for this scenario.
如您所料，可以通过几种方式为该场景构建DataStage作业。
The metadata browser imports the Salesforce object and field definitions into DataStage.
元数据浏览器可以将 Salesforce对象和字段定义导入到 DataStage 中。
The table will be empty until you complete and successfully run your full DataStage job.
（该表将为空，直到完成并成功运行完整的DataStage 作业）。
In this case, you need to instruct DataStage to collect all information for each account.
在本例中，需要命令DataStage收集每个帐户的所有信息。
The quality stages within the DataStage can cleanse the data and remove erroneous records.
DataStage中的quality stage可以清洗数据，移除错误的记录。
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